Pandas: 将数组列转换为 numpy 矩阵

Question

我有以下格式的数据：

Col1   Col2       Col3
1,    1424549456, "3 4"
2,    1424549457, "2 3 4 5"

& 已成功将其读入 pandas。

如何将 Col3 转换为以下形式的 numpy 矩阵：

# each value needs to become a 1 in the index of the col
# i.e. in the above example 3 is the 4th value, thus
# it is [0 0 0 1]  [0 indexing is included]
mtx = [0 0 0 1 1 0    # corresponds to first row
       0 0 1 1 1 1];  # corresponds to second row

感谢您提供的任何帮助！

Answer 1

如果数据不多，您可以执行类似

的操作

res = []
def f(v):
    r = np.zeros(6, np.int)
    r[map(int, v.split())] = 1
    res.append(r)
df.Col3.apply(f)
mat = np.array(res)

# if you really want it to be a matrix, you can do
mat = np.matrix(res)

查看this link了解更多信息

Answer 2

Since 0.13.1 there's str.get_dummies:

In [11]: s = pd.Series(["3 4", "2 3 4 5"])

In [12]: s.str.get_dummies(sep=" ")
Out[12]:
   2  3  4  5
0  0  1  1  0
1  1  1  1  1

您必须确保列是整数（而不是字符串）并重新索引：

In [13]: df = s.str.get_dummies(sep=" ")

In [14]: df.columns = df.columns.map(int)

In [15]: df.reindex(columns=np.arange(6), fill_value=0)
Out[15]:
   0  1  2  3  4  5
0  0  0  0  1  1  0
1  0  0  1  1  1  1

要获取 numpy 值，请使用 .values:

In [16]: df.reindex(columns=np.arange(6), fill_value=0).values
Out[16]:
array([[0, 0, 0, 1, 1, 0],
       [0, 0, 1, 1, 1, 1]])

Pandas: 将数组列转换为 numpy 矩阵

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